skills-audit

Name: skills-audit
Availability: InStock
Author: xwtro0tk1t-cloud

Analyze AI agent skills for security risks and prioritized remediation.

316|42|Updated Apr 5, 2026

Search Tags:#security #audit #ai #compliance #policy #risk #threat

Ready to run

npx skills add https://github.com/xwtro0tk1t-cloud/harness --skill skills-audit-xwtro0tk1t-cloud

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: skills-audit
Source: https://github.com/xwtro0tk1t-cloud/harness/tree/main/bundled-skills/skills-audit
Command: npx skills add https://github.com/xwtro0tk1t-cloud/harness --skill skills-audit-xwtro0tk1t-cloud

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

The Security Audit Skill helps teams identify and mitigate vulnerabilities in AI agent skills, including malware risks, prompt injection, data leaks, and supply-chain weaknesses.

Core Features & Use Cases

Comprehensive artifact analysis and threat-hunting across code, prompts, dependencies, and external references.
AI semantic risk assessment combined with static pattern matching and deep code understanding.
Typical use cases include auditing third-party skills, validating suspicious behaviors, and enforcing security policies.

Quick Start

Analyze a target skill directory with the audit engine to obtain a security risk score and actionable remediation guidance.

Frequently Asked Questions about skills-audit

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I audit AI agent skills for security risks and prompt injection?▼

To audit AI agent skills for security risks, you analyze skill artifacts, prompts, and dependencies to detect vulnerabilities like prompt injection and data leaks. The audit engine combines static pattern matching with AI semantic risk assessment to return structured remediation guidance.

What is AI semantic risk assessment in skill security audits?▼

AI semantic risk assessment is a mechanism that evaluates the contextual meaning and behavior of prompts and code to identify subtle threats. Unlike basic static pattern matching, it detects complex vulnerabilities such as indirect prompt injection and unauthorized data exfiltration attempts.

How to validate third-party AI skills for malware and supply-chain weaknesses?▼

To validate third-party AI skills for malware and supply-chain weaknesses, run the target skill directory through the audit engine. It performs comprehensive artifact analysis and threat-hunting across external references to generate a prioritized risk score and actionable fixes.

Can I enforce security compliance policies for AI agent skills?▼

Yes, you can enforce security compliance policies for AI agent skills by auditing artifacts against established threat intelligence. The process identifies policy violations across code and dependencies, returning a structured risk assessment with prioritized findings to ensure compliance.

What is the best way to detect data leak vulnerabilities in AI prompts?▼

The best way to detect data leak vulnerabilities in AI prompts is using an audit engine that combines deep code understanding with semantic risk analysis. This approach identifies unauthorized external references and data exfiltration paths, providing prioritized remediation recommendations.

What are the limitations of static pattern matching for AI threat detection?▼

Static pattern matching alone often misses complex AI semantic risks like indirect prompt injection because it lacks contextual understanding of prompt behavior. Combining static analysis with deep semantic threat intelligence is necessary to identify nuanced vulnerabilities and supply-chain weaknesses.